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Proceedings Paper

Methods for object tracking and shadowing in a top-down view virtual reality scattered radiation display system (SDS) for fluoroscopically-guided procedures
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Paper Abstract

We have developed a prototype scatter-display system (SDS) which includes a top-down view, virtual reality (VR) representation of an interventional room containing a color-coded scatter dose rate distribution in real-time. To represent various attenuating objects of interest in the room, such as the C-Arm gantry and ceiling mounted shield, the STL toolbox in Matlab was implemented to produce a 3D VR description of the objects. Attenuation by objects in the room will alter the dose distribution and may lead to shielding of individual staff members, and thus representation of those objects in the software is needed for precise dose rate estimations. Determination of the spatial regions of attenuation requires accurate specification of object position. To retain identification of a ceiling mounted shield, we implemented an open-source package which maintains object recognition using the depth camera feed of a Microsoft Kinect V2 and the features-from-accelerated-segment- test (FAST) algorithm in OpenCV for a dense sampling of salient features. The depth information from the identified object is transferred to an open-source robot operating system (ROS) wrapper for specification of the 3D position to be fed into the SDS. To compute the C-Arm gantry position, we take advantage of a controller area network (CAN) bus interfaced with the angiography system’s application programming interface (API). Methods for computing gantry and ceiling mounted shield shadow regions are discussed and demonstrated. FAST was applied to the ceiling-shield assembly’s flange with reliable recognition. Including object attenuation of room scatter in the SDS will facilitate accurate dose rate computation.

Paper Details

Date Published: 16 March 2020
PDF: 14 pages
Proc. SPIE 11312, Medical Imaging 2020: Physics of Medical Imaging, 113123C (16 March 2020); doi: 10.1117/12.2548469
Show Author Affiliations
J. Troville, The State Univ. of New York at Buffalo (United States)
C. Guo, The State Univ. of New York at Buffalo (United States)
S. Rudin, The State Univ. of New York at Buffalo (United States)
D. R. Bednarek, The State Univ. of New York at Buffalo (United States)

Published in SPIE Proceedings Vol. 11312:
Medical Imaging 2020: Physics of Medical Imaging
Guang-Hong Chen; Hilde Bosmans, Editor(s)

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